Document classification in structured military messages

Document Classification in Structured Military Messages Abstract We present new results for the DSTO project on document classification of military messages. We report more specifically on the improvements to the Part-Of-Speech (POS) tagging, probabilistic process that assigns a tag to a a token, and discuss the training for Date Time Groups POS tags. A new implementation of the rule-based classifier is described. The results obtained on two databases of real military messages are encouraging and the document classification module has now been integrated with a query user interface. 1 Introduction In (Carr and Estival, 2002), we presented the first tentative results of the Document Classification project we have been conducting at DSTO and we discussed the shortcomings of the approach we were using. In this paper, we present the results we have obtained in the continuation of that project, after having implemented improvements in the POS tagging component and taken a different approach for the rule-based classifier component. These results show that rule-based classifiers can give reasonable results for structured textual information, when using appropriate language models for POS tagging. 1.1 Goals of the project A large part of the Defence Information Environment (DIE) used at the Deployable Joint Force Headquarters (DJFHQ) is based on Lotus collaborative and messaging applications. The staff members of DJFHQ use Lotus databases to log operational events and Lotus e-mail for actions and administrative functions. Around 200 messages per day are entered into these Lotus Notes log databases. Many DJFHQ staff members have expressed difficulty in finding particular information in their information reservoirs and our goal is to develop a more effective query interface between DJFHQ staff and their information reservoirs. This work already resulted in the development of the Query Building Interface (QBI), which was designed to create a better search interface to multiple log databases and to the users e-mail database. The rule-based Document Classifier we describe here has been trained and evaluated on Lotus operational log databases (OPS logs) from DJFHQ. It can now provide a categorisation for each document from the OPS logs and is integrated with QBI, as described in Section 7.2. 1.2 Proposed Architecture Fig.1 below shows how QBI and the Document Classifier could be integrated in the existing IT infrastructure. In this new Server Environment, both QBI and the Document Classifier interface with the Lotus Notes database. Lotus Notes Client Lotus Databases Lotus E-mail Speech Synthesis Query Building Interface OPS Log User Document Classifier PC's Server Environment Fig.1 Proposed Architecture In this architecture, users enter and access documents through Lotus Notes as they do now, and they receive notification of the document classification. One possible scenario is to use a Text-to-Speech module to warn of the arrival of Oliver Carr and Dominique Estival Human Systems Integration Group Command and Control Division Defence Science and Technology Organisation {Oliver.Carr,Dominique.Estival}@dsto.defence.gov.au some pre-specified document types, eg. NOTICAS (Notification of Casualty) or MEDSITREP (Medical Situation Report). For a NOTICAS, the injured person's details could be automatically retrieved and read out to the Commander …

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